Two kinds of material, one standard: deep-dive guides written by the people who do the work, and short field notes built from real questions businesses send us — anonymized, because if one company is asking, twenty more are wondering. No listicles, no keyword-chasing. New notes land several times a week.
Short answers to real questions, several times a week. The question as received (anonymized), what we told them, and the takeaway.
Read the noteA client piloting an AI coding assistant asked if it could be talked into a real attack. The same week, hackers proved the answer is yes.
Read the noteA team that barely touches GitHub found out during an 8-hour outage that GitHub had been quietly running their front door the whole time. What we told them to check.
Read the noteAn old AWS key in a public JS file, and a CRM platform whose entire customer database was gone in 90 minutes because of one just like it. What we told them to do about theirs.
Read the noteA critical flaw hit the automation platform running their workflows. What we told them — and why the tool orchestrating your CRM and inbox needs the same patch discipline as a server.
Read the noteUsage looked flat but the bill nearly doubled. Retry loops and tool-call chaining rack up cost without ever throwing an error — here's how to cap it before the invoice tells you.
Read the noteAn AI ran an entire network intrusion in under an hour, no human steering. Why "too small to be a target" is over — and the unglamorous defenses that actually work.
Read the note"The first real invoice had usage charges nobody understood." Seats vs. tokens, the retry loop that burns money overnight, and how to budget AI like cloud.
Read the noteAn agent that can send email and update your CRM can also do both wrong. The three checkpoints that stop it, and the one question that exposes a vendor who skipped them.
Read the noteNew campaigns test stolen Microsoft credentials without tripping the failed-sign-in alerts your defenses watch for. What to check on your tenant this week.
Read the noteRaters once preferred a tuned model over one a hundred times its size. Why "what was it tuned to do" beats "how big is it" — and the two questions to ask before you pick.
Read the noteA 95%-reliable step chained ten times succeeds about 60% of the time. The arithmetic that says when a plain workflow beats an autonomous agent — which is most of the time.
Read the noteIt backs whoever asked, because it was trained on human preferences — and people often prefer confident agreement over correction. How to get honest output anyway.
Read the note"Every tool we've been pitched this year calls itself an AI agent. Is there an actual definition, or is it all marketing?" There is — one sentence, and a test you can run in any demo.
Read the note"The price is a multiple of the model's API costs — what's actually in the stack?" Four layers: brain, hands, notebook, and the safety wrapper. The demo shows one; the invoice is the other three.
Read the noteCornerstone pieces, deep enough to be worth your time. Each took 8–12 hours to write because the questions are worth taking seriously.
The prompts we actually use, collected in one place — research, marketing, operations, writing, productivity. Fill in your variables once, hit Copy, and drop them into Claude, ChatGPT, or Gemini. Growing as we find prompts worth keeping.
A five-step framework for getting real value from AI without leaking data, racking up compliance debt, or buying into the next vendor lock-in. Written for operators who want to move fast and stay defensible.
Read the playbookMost MSP sales calls ask you to fill in a discovery form. The right ones are willing to be discovered themselves — and most aren't ready for it. Here's the question set that separates serious providers from the ones repackaging the same RMM toolkit.
Read the guideWhen we onboard a new client and audit their existing M365 tenant, the same configuration gaps appear over and over. Half of them take 5 minutes to fix and dramatically reduce attack surface. Here's the list, with exactly what to check.
Read the auditEvery business has been pitched "AI." Most of those pitches were chatbots wearing a 2024 sweater. Here's the actual distinction that matters — what agents do that chatbots don't, and which use cases pay back the investment vs. which ones are still demos pretending to be products.
Read the breakdownThe reason most businesses stay too long with a bad MSP is not loyalty or sunk cost — it's fear of the switch. Here's the nine-phase playbook for transitioning between providers with zero production outage, including the identity handoff most transitions skip and what to do when the outgoing MSP gets difficult.
Read the playbookIf you've got a technology question the existing internet doesn't answer well, send it over. The best ones become notes — anonymized — and you get a straight answer either way.